Knowing Your Customers: the challenge of creating a single customer view
External data from banks, market data providers, and regulators can often be confusing if they all use different codes to identify the same entity.
Internal customer data flows from different departments can create duplicate, erroneous and incomplete client data – which can lead to costly mistakes. What makes the situation even more confusing is the availability of both internal and external data.
In an ideal world, every legal entity or structure, in any jurisdiction, that is party to a financial transaction should have a Legal Entity Identifier (“LEI”). Disappointingly, LEI coverage is sporadic both in terms of the types of entities that have LEIs and geographical coverage. What’s more, only a few regulations currently mandate their usage – like Dodd-Frank and EMIR.
Financial institutions are finding the current raft of new and impending rules and regulations extremely challenging – forcing them to create a more consistent and comprehensive view of all the entities that they deal with. The accuracy of client and counterparty information is critical, not only to satisfy regulatory requirements, but also to ensure that firms have a complete view of who they are dealing with.
Having a single view of a customer or counterparty would help banks understand what business they do with them, and more importantly, how to create better custom. The problem lies in the number of entity identifiers that each customer and counterparty can have inside a firm. A salesperson, trader and investment banker may all use different identifiers for the same client, and not know the full picture of all relationships that carry on concurrently – aside from within their own silo.
A greater deal of resource – data, staff and IT infrastructure – are used to clean, cross-reference and cross-match client data in the hope that a firm can make better sense of their customer relationships. Even after this is done, the data may still be flawed because the data from various places was not correct in the first place.
In an ideal world, there needs to be a central “golden source” for entity data which is constantly refreshed with internal data – and validated against external data sources. Mapping these data sources together can help firms meet their regulatory requirements. There is a business case for creating this golden source of all possible clients and counterparties, because this would show all the business linkages between any entity and the firm.
A single view of customer data is becoming a key requirement for the compliance, credit risk management, sales and marketing functions. Within many financial institutions, client accounts, trades capture and market data is stored in different databases. This can lead to an inconsistent approach to the same client when providing different types of services.
In an ideal world, firms can perform entity identifier mapping and be able to match client accounts and counterparty information with trades capture and market data. This is easier said than done because a big obstacle is going to be the various disparate systems and silos that exist in many institutions. What’s more, the basic data attribute – the entity name – is often the big problem. Entities names are sometimes duplicated or entered into a system in a variety of names. Only expert matching techniques can reveal the true identity of an entity.
Entity names and attributable data never stays the same. The challenge is to keep the entity record as up to date as possible. It is not unusual for companies to experience a series of corporate actions over any given period of time. Change in registered office addresses or M&A can affect the way an entity is handled internally – either from a regulatory standpoint or from a risk perspective. If a client moves from London to Monaco, this would not only affect the type of KYC and onboarding process that is required but could also throw-up regulatory implications too.
All entities should have a regulatory status as part of a bank’s risk management framework – and this would determine the effort involved in onboarding an entity. If an entity is regulated by a recognized regulator, they would normally be considered lower risk – and therefore require less KYC. The problem is keep up with the pace of regulation and also any changes with the regulatory status of an entity.
If firms invest in creating a single view of a customer, not only will the management of entity data and KYC be a lot easier, it will also lower the cost of owning and managing client data, with a consistent approach to satisfy regulation.
Author: Steve Tang, Senior Consultant, Axis Corporate email@example.com
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